Impact of the AI Dependency Revolution on Both Physical and Mental Health

Authors

  • Kashish Ali University of Texas at San Antonio
  • Autumn Garcia University of Texas at San Antonio
  • Alina Vadsariya University of Texas at San Antonio

DOI:

https://doi.org/10.33423/jsis.v19i2.7006

Keywords:

innovation, sustainability

Abstract

Artificial intelligence (AI) offers capabilities beyond human performance, which has led to the global transformation of various industries, sectors, and other elements of our daily lives. Whether we use an application like Siri to send a text message or facial recognition to access a device, AI is an integral part of everyday technology. Artificial Intelligence has especially been integrated into various healthcare sectors, improving patient health outcomes and overall healthcare delivery. Diagnostic AI systems enhance clinical decision-making, personalizing treatment, and reducing stigma. However, its extensive use raises concerns about dependency, credibility, and its effects on physical and mental health. This research explores the advantages and drawbacks of AI dependency, emphasizing the need to use AI judiciously to safeguard decision-making capabilities. Additionally, trust and confidence in AI is vital for its successful implementation in healthcare. In mental health, AI offers promise for early detection and personalized treatment, addressing accuracy and accessibility limitations. To fully harness AI’s potential, ethical concerns, data privacy, and algorithmic bias must be addressed to harness AI’s potential in mental health care.

References

Agapito, M., Aquino, Q.M., Barreiro, M.S., Riolivia, C., Quitalig, N.H., & Narvaez, R.A. (2023, July 1). Role of artificial intelligence and its impact in mental health services. HIMSS. Retrieved from https://www.himss.org/resources/role-artificial-intelligence-and-its-impact-mental-health-services

Ahmad, S.F., Han, H., Alam, M.M., Rehmat, M.K., Irshad, M., Arraño-Muñoz, M., & Ariza-Montes, A. (2023). Impact of artificial intelligence on human loss in decision making, laziness and safety in education. Humanities and Social Sciences Communications, 10(1), 1–14. https://doi.org/10.1057/s41599-023-01787-8

Asan, O., Bayrak, A.E., & Choudhury, A. (2020). Artificial intelligence and human trust in healthcare: Focus on clinicians. Journal of Medical Internet Research, 22(6), e15154–e15154. https://doi.org/10.2196/15154

Ayers, J.W., Zhu, Z., Poliak, A., Leas, E.C., Dredze, M., Hogarth, M., & Smith, D.M. (2023). Evaluating artificial intelligence responses to public health questions. JAMA Network Open, 6(6), e2317517–e2317517. https://doi.org/10.1001/jamanetworkopen.2023.17517

Barth, S. (2022). Artificial Intelligence (AI) in Healthcare & Hospitals. ForeSee Medical. Retrieved from https://www.foreseemed.com/artificial-intelligence-in-healthcare

Bohr, A., & Memarzadeh, K. (2020). The rise of artificial intelligence in healthcare applications. Artificial Intelligence in Healthcare, pp. 25–60. https://doi.org/10.1016/B978-0-12-818438-7.00002-2

Campion, A., Gasco-Hernandez, M., Jankin Mikhaylov, S., & Esteve, M. (2022). Overcoming the challenges of collaboratively adopting artificial intelligence in the public sector. Social Science Computer Review, 40(2), 462–477. https://doi.org/10.1177/0894439320979953

Choudhury, A., & Asan, O. (2020). Role of artificial intelligence in patient safety outcomes: Systematic literature review. JMIR Medical Informatics, 8(7), e18599. https://doi.org/10.2196/18599

Ćosić, K., Popović, S., Šarlija, M., Kesedžić, I., & Jovanovic, T. (2020). Artificial intelligence in prediction of mental health disorders induced by the COVID-19 pandemic among health care workers. Croatian Medical Journal, 61(3), 279–288. https://doi.org/10.3325/cmj.2020.61.279

D’Alfonso, S. (2020). AI in mental health. Current Opinion in Psychology, 36, 112–117. https://doi.org/10.1016/j.copsyc.2020.04.005

Dave, M., & Patel, N. (2023). Artificial intelligence in healthcare and education. British Dental Journal, 234(10), 761–764. https://doi.org/10.1038/s41415-023-5845-2

Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94.

Dwyer, D.B., Falkai, P., & Koutsouleris, N. (2018). Machine learning approaches for clinical psychology and psychiatry. Annual Review of Clinical Psychology, 14, 91–118.

Ehsan, U., Liao, Q.V., Muller, M., Riedl, M.O., & Weisz, J.D. (2021). Expanding Explainability: Towards Social Transparency in AI systems. https://doi.org/10.1145/3411764.3445188

Ergen, M. (2019). What is artificial intelligence? Technical considerations and future perception. Anatolian Journal of Cardiology, 22(Suppl 2), 5–7. https://doi.org/10.14744/AnatolJCardiol.2019.79091

Firth, J., Torous, J., & Yung, A.R. (2016). Ecological momentary assessment and beyond: The rising interest in e-mental health research. J Psychiatr Res, 80, 3–4.

Fisher, S., & Rosella, L.C. (2022). Priorities for successful use of artificial intelligence by public health organizations: A literature review. BMC Public Health, 22(1). https://doi.org/10.1186/s12889-022-14422-z

Ganapathi, S., Palmer, J., Alderman, J.E., Calvert, M., Espinoza, C., Gath, J., . . . Liu, X. (2022). Tackling bias in AI health datasets through the STANDING Together initiative. Nature Medicine, 28(11), 2232–2233. https://doi.org/10.1038/s41591-022-01987-w

Graham, S., Depp, C., Lee, E.E., Nebeker, C., Tu, X., Kim, H.C., & Jeste, D.V. (2019). Artificial intelligence for mental health and mental illnesses: An overview. Current Psychiatry Reports, 21, 1–18.

Haresamudram, K., Larsson, S., & Heintz, F. (2023). Three Levels of AI Transparency. Computer, 56(2), 93–100. Long Beach, Calif. https://doi.org/10.1109/MC.2022.3213181

HealthITSecurity. (2021, April 23). What Role Could Artificial Intelligence Play in Mental Healthcare? HealthITAnalytics. Retrieved from https://healthitanalytics.com/features/what-role-could-artificial-intelligence-play-in-mental-healthcare

Jansson, M., Ohtonen, P., Alalääkkölä, T., Heikkinen, J., Mäkiniemi, M., Lahtinen, S., . . . Liisantti, J. (2022). Artificial intelligence-enhanced care pathway planning and scheduling system: Content validity assessment of required functionalities. BMC Health Services Research, 22(1), 1513.

Jungwirth, D., & Haluza, D. (2023). Artificial intelligence and public health: An exploratory study. International Journal of Environmental Research and Public Health, 20(5), 4541. https://doi.org/10.3390/ijerph20054541

Kennedy, B., Tyson, A., & Saks, E. (2023, February 15). Public Awareness of Artificial Intelligence in Everyday Activities. Pew Research Center Science & Society. Retrieved from https://www.pewresearch.org/science/2023/02/15/public-awareness-of-artificial-intelligence-in-everyday-activities/

Liu, B. (2021). In AI we trust? Effects of agency locus and transparency on uncertainty reduction in human–ai interaction. Journal of Computer-Mediated Communication, 26(6), 384–402. https://doi.org/10.1093/jcmc/zmab013

Luxton, D.D., Anderson, S.L., & Anderson, M. (2016). Ethical issues and artificial intelligence technologies in behavioral and mental health care. In Artificial Intelligence in Behavioral and Mental Health Care (pp. 255–276). Academic Press.

Marr, B. (n.d.). AI In Mental Health: Opportunities and Challenges in Developing Intelligent Digital Therapies. Forbes. Retrieved September 17, 2023, from https://www.forbes.com/sites/bernardmarr/2023/07/06/ai-in-mental-health-opportunities-and-challenges-in-developing-intelligent-digital-therapies/?sh=3e7cf7ab5e10

McKendrick, J., & Thurai, A. (2022, September 15). AI Isn’t Ready to Make Unsupervised Decisions. Harvard Business Review. Retrieved from https://hbr.org/2022/09/ai-isnt-ready-to-make-unsupervised-decisions

Mesko, B. (2017). The role of artificial intelligence in precision medicine. Expert Review of Precision Medicine and Drug Development, 2(5), 239–241.

Moreno, S. (2023, March 9). Growth of AI in mental health raises fears of its ability to run wild. Axios. Retrieved from https://www.axios.com/2023/03/09/ai-mental-health-fears

Naik, N., Hameed, B.M., Shetty, D.K., Swain, D., Shah, M., Paul, R., . . . Somani, B.K. (2022). Legal and ethical consideration in artificial intelligence in healthcare: who takes responsibility? Frontiers in Surgery, 9, 266.

Nazer, L.H., Zatarah, R., Waldrip, S., Ke, J.X.C., Moukheiber, M., Khanna, A.K., . . . Mathur, P. (2023). Bias in artificial intelligence algorithms and recommendations for mitigation. PLOS Digital Health, 2(6), e0000278–e0000278. https://doi.org/10.1371/journal.pdig.0000278

Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447–453. American Association for the Advancement of Science. https://doi.org/10.1126/science.aax2342

Price, W.N., & Cohen, I.G. (2019). Privacy in the age of medical big data. Nature Medicine, 25(1), 37–43.

Ray, A., Bhardwaj, A., Malik, Y.K., Singh, S., & Gupta, R. (2022). Artificial intelligence and Psychiatry: An overview. Asian Journal of Psychiatry, 70, 103021.

Ryan, M. (2020). In AI we trust: Ethics, artificial intelligence, and reliability. Science and Engineering Ethics, 26(5), 2749–2767. https://doi.org/10.1007/s11948-020-00228-y

Suarjana, I.W.G., Sudirham, Salam, I., & Aditama, M.H.R. (2023). Artificial intelligence in public health: The potential and ethical considerations of artificial intelligence in public health. Journal of Public Health. Oxford, England. https://doi.org/10.1093/pubmed/fdad116

Sun, T.Q., & Medaglia, R. (2019). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368–383. https://doi.org/10.1016/j.giq.2018.09.008

Taddeo, M., & Floridi, L. (2018). How AI can be a force for good. Science, 361(6404), 751–752.

Tegenu Lemma, K., Tilahun Beyene, D., Mekoya Jemaneh, T., Melkamu Andualem, E., & Atomsa Hunde, G. (2023). Patients’ trust in health care providers among hospitalized patients, Jimma, South West Ethiopia. SAGE Open Nursing, 9, 23779608231167810–23779608231167810. https://doi.org/10.1177/23779608231167810

Terra, M., Baklola, M., Ali, S., & El-Bastawisy, K. (2023). Opportunities, applications, challenges and ethical implications of artificial intelligence in psychiatry: A narrative review. The Egyptian Journal of Neurology, Psychiatry and Neurosurgery, 59(1), 1–10.

Vokinger, K.N., & Gasser, U. (2021). Regulating AI in medicine in the United States and Europe. Nature Machine Intelligence, 3(9), 738–739.

Wani, S.U.D., Khan, N.A., Thakur, G., Gautam, S.P., Ali, M., Alam, P., . . . Shakeel, F. (2022). Utilization of artificial intelligence in disease prevention: Diagnosis, treatment, and implications for the healthcare workforce. Healthcare, 10(4), 608. Basel. https://doi.org/10.3390/healthcare10040608

Downloads

Published

2024-06-05

How to Cite

Ali, K., Garcia, A., & Vadsariya, A. (2024). Impact of the AI Dependency Revolution on Both Physical and Mental Health. Journal of Strategic Innovation and Sustainability, 19(2). https://doi.org/10.33423/jsis.v19i2.7006

Issue

Section

Articles